Twitter Mapping: Foundations

With more than 500 million tweets sent every day, Twitter data as a whole can seem huge and unimaginable, like cramming the contents of the Library of Congress into your living room.

One way of trying to make that big data understandable is by making it smaller and easier to handle by giving it context; by putting it on a map.

It’s something I do a lot—I’ve published over 1,000 maps in the past five years, mostly at Guardian Data. At Twitter, with 77% of users outside the US, it’s often aimed at seeing if regional variations can give us a global picture, an insight into the way a story spreads around the globe. Here’s what I’ve learned about using Twitter data on maps.

… (lots of really cool maps and links omitted)

Creating data visualizations is simpler now than it’s ever been, with a plethora of tools (free and paid) meaning that any journalist working in any newsroom can make a chart or a map in a matter of minutes. Because of time constraints, we often use CartoDB to animate maps of tweets over time. The process is straightforward—I’ve written a how-to guide on my blog that shows how to create an animated map of dots using the basic interface, and if the data is not too big it won’t cost you anything. CartoDB is also handy for other reasons: as it has access to Twitter data, you can use it to get the geotagged tweets too. And it’s not the only one: Trendsmap is a great way to see location of conversations over time.

Have you made a map with Twitter Data that tells a compelling story? Share it with us via @TwitterData.

While composing this post I looked at CartoDB solution for geotagged tweets and while impressive, it is currently in beta with a starting price of $300/month. Works if you get your expenses paid but a bit pricey for occasional use.

There is a free option for CartoDB (up to 50 MB of data) but I don’t think it includes the twitter capabilities.

Sample mapping tweets on your favorite issues. Maps are persuasive in ways that are not completely understood.

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on Sunday, October 12th, 2014 at 10:32 am and is filed under Mapping, Maps, Tweets.
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